Chief Data Engineer

CACI International Inc is seeking a Chief Data Engineer to support the Department of Homeland Security Office of the Inspector General. The role leads the architecture and development of a secure, cloud-based enterprise data platform, oversees data pipeline modernization and integration, and manages data engineering resources supporting analytics, AI, governance, and national security operations.

Responsibilities:

• Lead the design, development, testing, and implementation of enterprise data ingestion and transformation pipelines that consolidate investigative records, hotline data, DHS datasets, and federal/commercial data sources into a centralized, governed data platform
• Oversee migration from legacy Informatica PowerCenter, Informatica Data Quality, and on-premises Python scripts to modern cloud-based data integration solutions using Azure Data Factory, Databricks, or equivalent technologies
• Architect and implement scalable data integration patterns supporting batch processing, incremental updates, streaming ingestion, and metadata-driven pipelines with comprehensive error handling and monitoring
• Lead ongoing operation, automation, monitoring, and reporting of production data pipelines, including performance optimization, failure remediation, data quality validation, and SLA compliance
• Design and implement integration with DHS data fabric, Delta Sharing, APIs, secure file transfer mechanisms, and data-sharing protocols while preserving DHS OIG independence and preventing unauthorized reciprocal access
• Coordinate phased data onboarding approach based on Government priorities, including technical discovery, source system analysis, data profiling, pipeline design, testing, and production deployment
• Provide technical leadership for data architecture and cloud analytics engineering, including lakehouse design, data modeling (relational, graph, geospatial), and optimization for analytical and AI workloads
• Lead and coordinate data engineering resources, including surge support for complex analytical needs, forensic data reconstruction, and specialized technical problem sets
• Develop and maintain comprehensive technical documentation including data lineage, pipeline architecture, integration specifications, operational runbooks, and data engineering best practices
• Collaborate with Government stakeholders, platform architects, AI engineers, and governance specialists to ensure data pipelines support mission analytics, comply with data governance policies, and enable AI model consumption of authoritative datasets

Requirements:

• Bachelor's degree + 15 years of experience in data engineering, data architecture, software engineering, or related field; equivalencies considered (Master's + 12 years; 21 years with no degree; AA + 17 years)
• Proven leadership experience architecting and delivering enterprise-scale data integration and ETL/ELT solutions with demonstrated ability to lead data engineering teams
• Deep expertise in cloud data engineering using Azure services (Azure Data Factory, Azure Databricks, Azure Data Lake, Azure Synapse) or equivalent AWS/GCP platforms
• Extensive hands-on experience with data pipeline development using Python, SQL, PySpark, and modern data integration frameworks with understanding of lakehouse architectures and Delta Lake
• Strong background in data architecture, data modeling, data quality, performance optimization, and operationalizing production data pipelines at scale
• Experience with Informatica PowerCenter, Informatica Data Quality, or other legacy ETL platforms and successful migration to cloud-native solutions
• Hands-on experience with DHS data fabric, Delta Sharing, or federal data-sharing mechanisms in secure government cloud environments (Azure Government, AWS GovCloud)
• Background in federal government, law enforcement, investigative, or national security data environments with understanding of sensitive data handling, data governance, and compliance requirements (NIST 800-53, FedRAMP)